Security Scan Report: www.cnbctv18.com

Submitted: Nov 20, 2025, 8:21:25 AMCompleted: Nov 20, 2025, 8:23:25 AMpubliccompleted
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Summary

This website contacted 98 IPs in 7 countries across 43 domains to perform 509 HTTP transactions. The main domain is cnbctv18.com and was registered NaN years ago.

Submitted URL: https://www.cnbctv18.com/india/miss-universe-india-2025-title-goes-to-rajasthans-manika-vishwakarma-19655718.htm

The Cisco Umbrella rank of the primary domain is #302,964 of the top 1 million websites

AI Security Verdict

High Risk

Confidence: 85%

6
Risk Score

Page shows brand content on a low‑ranked domain and has a circular redirect, indicating high‑risk phishing potential.

Risk Factors
Circular redirect detected (strong indicator of URL manipulation)
Low ranking domain (rank 302,964) claiming a well‑known brand (potential brand impersonation)
Domain age information unavailable

Details

Page Title

Miss Universe India 2025 title goes to Rajasthan’s Manika Vishwakarma - CNBC TV18

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news media journalism

(70%)

Domain Information

The domain 'www.cnbctv18.com' uses the commercial generic top-level domain (.com); it also runs on subdomain 'www'. The registrable portion 'cnbctv18' spans 8 characters with zero vowels and 6 consonants, plus 2 digits. Word splitting yields three words: cnbc, tv, 18. Expect 2 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.cnbctv18.com/india/miss-universe-india-2025-title-goes-to-rajasthans-manika-vishwakarma-19655718.htm

Page Load Overview

2.74s
Total Load Time
509
HTTP Requests
43
Domains
13.3 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:47,964 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism70% confidence
Type: static
Method: ml+structural

All Detected Categories

news media journalism
70%
corporate business
50%
cryptocurrency blockchain
43%
government public service
37%
news/blog
35%

Detected Features

Search
Articles
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
141146.75.121.44Frankfurt am Main, Hesse, Germany
AS54113FASTLY
93104.75.90.126Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
9223.32.238.169Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
342.18.64.221Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
24141.226.228.48Netherlands
AS200478Taboola.com ltd
21146.75.120.157Frankfurt am Main, Hesse, Germany
AS54113FASTLY
20146.75.120.158Frankfurt am Main, Hesse, Germany
AS54113FASTLY
10216.58.212.131United States
AS15169GOOGLE
723.32.238.211Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
6142.250.186.110United States
AS15169GOOGLE
50998--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T134443B338965222EE53BDAC437F43F5EA255C02BD481AFD9F6D56924CFCB9C5062230A

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:cn6ceZMBzXnz6qJuz3s3he0n5kY90+Mcn1bKv2PmB2yEaxeoOK+A9OpNDtdP8:rDZMBzXnz6qJuz3s3he0n5kY90+Mcn1U

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:273505:JgAJwQhkgAJlwRX3CUkBEgoDPKG3Qg4YawwGAkVbRCqpMAhCAJozDKZxTFsQdhgQmIDAKFkcRBggOkIQzAEF+oAnrgKSAiQE

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:0000ffe7e1fdffff
Perceptual Hash:e3321c496336cbcb
Difference Hash:d9d149cccbe37c14
Wavelet Hash:0000e7c3c1f9ff97
Color Hash:#c5b187

Scan History

Scan history not available

Unable to load historical scan data